Mid-Level Business Intelligence Analyst - Dallas, TX

Job Description

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Job Description

At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.

The Boeing Company is currently seeking a Mid-Level Business Intelligence Analyst to join the team in Seattle, WA;
Berkeley, MO;
Hazelwood, MO; or Dallas, TX.

Partners in the design of Business Intelligence information models, dashboards, metrics and reports using standard technologies and methodologies that meet business objectives. Combines SQL, Business Intelligence (BI) best practices, cloud data engineering awareness, and domain knowledge to deliver efficient and scalable BI solutions that improve productivity and business outcomes. This role is primarily a BI Analyst role but requires practical familiarity with Generative Artificial Intelligence (GenAI) and prompt engineering techniques to accelerate analytics, automate workflows, and prototype Large Language Model (LLM)-enabled features.

Position Responsibilities:

Design reusable BI information models, views, dashboards, metrics and reports that meet business needs across supply chain and related functions

Translate business requirements into technical designs, user stories and acceptance criteria; validate delivered solutions with stakeholders

Build, optimize and maintain SQL (Redshift/Oracle/Teradata/SQL Server) queries, Extract Transfer Load (ETL)/data wrangling pipelines and data transformations for reliable reporting

Produce analytics deliverables (ad-hoc analysis, trend reports, root-cause investigations) to support decision-making

Prototype and evaluate GenAI/LLM use cases to augment BI workflows (e.g., natural-language querying, automated data summarization, intelligent insights generation, prompt templates for analysts)

Apply prompt engineering best practices: design, test, and optimize prompts and chains for consistent, accurate outputs; document prompt libraries and guardrails

Integrate LLM/GenAI capabilities with BI tools or data platforms where appropriate (e.g., Application Programming Interfaces (APIs), wrappers, microservices) in collaboration with engineers and data scientists

Ensure responsible use of GenAI: implement data privacy, Personally Identifiable Information (PII) handling, output validation, and model risk mitigation practices

Collaborate with data scientists, Machine Learning (ML) engineers, and platform teams on product ionizing Artificial Intelligence (AI)-enabled features and understanding model performance and limitations

Develop and deliver stakeholder-facing demos, playbooks, and training materials that show how GenAI augments BI workflows

Work with cloud data platforms (Google Cloud Platform (GCP) and Amazon Web Services (AWS)) to design, develop, and maintain data products - including data ingestion, storage, transformation, and serving layers

Build and validate data products on cloud platforms (Big Query, Cloud Storage, Dataflow, AWS S3, Redshift, Glue, etc.) and collaborate with platform/engineering teams on deploying them to production

Participate in agile delivery: sprint planning, estimation, development, testing and release activities

Identify opportunities to improve automation, reduce analyst toil, and scale analysis via templated assets and self-service

Additional Qualifications/Responsibilities

Basic Qualifications (Required Skills/Experience):

5+ years of experience in Business Intelligence, Analytics, or Data Engineering roles

Experience with SQL and relational databases (Oracle, Teradata, SQL Server)

Experience working with cloud platforms (GCP and/or AWS)

Experience with core data services (storage, ETL/streaming, warehouses, serverless computing)

Experience building data products on cloud platforms (ingestion, transformation, cataloging, serving)

Experience with BI/visualization tools such as Tableau and/or Power BI and ability to design scalable dashboards and data models

Experience with Python and/or R for data preparation, analysis, and/or prototyping

Experience with data modeling, ETL patterns, data quality practices, and common BI architecture

Experience with Agile, Dev Ops and release methodologies

Preferred Qualifications (Desired Skills/Experience):

Master's degree in computer science, Information Systems, Data Science, Business Analytics, or related field

Experience with strong communication skills with the…